The present invention relates to a medical inspection method using magnetic resonance, and more particularly to an NMR spectroscopic analyzing method favorable for the processing of an obtained spectrum.
In a nuclear magnetic resonance inspection apparatus for medical use in the prior art, measuring an NMR spectrum is expected to provide effective information for diagnosis. In this case, however, improvement of the SN ratio (signal-to-noise ratio) is limited because natural abundance of a material as an object for inspection is small and a time allowed to be used for the measurement is limited. On the other hand, in an NMR spectroscopy for medical use, the number of spectrum components usually contained and the resonant frequencies thereof are previously known in most cases.
Consequently, utilizing such previously known data, effective information for the diagnosis may be taken even from spectrum data having a bad SN ratio. A method of processing spectrum data based on such an idea is discussed in "Magnetic Resonance in Medicine", vol. 3, pp. 97-104, (1986).
According to this method, if the number of contained spectrum components is made K, the resonant frequency of the k-th spectrum component is made .omega..sub.k, the amplitude is made A.sub.k, the decay constant is made b.sub.k, and the phase is made .phi..sub.k, the obtained free induction decay (hereinafter abbreviated as "FID") can be formulated as ##EQU1## In the above-mentioned article, assuming that b.sub.k, .omega..sub.k are known previously, A.sub.k which seems to include .phi..sub.k and effective information for the diagnosis is determined from the actual measured data G(t) of the FID by the method of least squares.
That is, if estimate values for .phi..sub.k, A.sub.k are made .phi..sub.k, A.sub.k and the FID calculated from these values is made F(t), A.sub.k and .phi..sub.k are determined so that ##EQU2## wherein b.sub.k, .omega..sub.k are already known. In this method, since b.sub.k, .omega..sub.k are already known, only A.sub.k, .phi..sub.k remain unknown, and these can be estimated if sufficient measuring points can be obtained.